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A conceptual framework for social movements analytics for national security

Lookup NU author(s): Professor Boguslaw ObaraORCiD

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This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by Springer Verlag, 2018.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

© Springer International Publishing AG, part of Springer Nature 2018. Social media tools have changed our world due to the way they convey information between individuals; this has led to many social movements either starting on social media or being organised and managed through this medium. At times however, certain human-induced events can trigger Human Security Threats such as Personal Security, Health Security, Economic Security or Political Security. The aim of this paper is to propose a holistic Data Analysis Framework for examining Social Movements and detecting pernicious threats to National Security interests. As a result of this, the proposed framework focuses on three main stages of an event (Detonating Event, Warning Period and Crisis Interpretation) to provide timely additional insights, enabling policy makers, first responders, and authorities to determine the best course of action. The paper also outlines the possible computational techniques utilised to achieve in depth analysis at each stage. The robustness and effectiveness of the framework are demonstrated by dissecting Warning Period scenarios, from real-world events, where the increase of Human Security aspects were key to identifying likely threats to National Security.


Publication metadata

Author(s): Cardenas P, Theodoropoulos G, Obara B, Kureshi I

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 18th International Conference on Computational Science (ICCS 2018)

Year of Conference: 2018

Pages: 302-315

Online publication date: 12/06/2018

Acceptance date: 02/04/2018

Date deposited: 04/05/2021

ISSN: 0302-9743

Publisher: Springer Verlag

URL: https://doi.org/10.1007/978-3-319-93698-7_23

DOI: 10.1007/978-3-319-93698-7_23

Library holdings: Search Newcastle University Library for this item

Series Title: Lecture Notes in Computer Science

ISBN: 9783319936970


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